Diaz Montana, C;
Cragg, W;
Choudhury, R;
Joffe, N;
Sydes, M;
Stenning, S;
(2019)
Implementing monitoring triggers and matching of triggered and control sites in the TEMPER study: A description and evaluation of a triggered monitoring management system.
Trials
, 20
, Article 227. 10.1186/s13063-019-3301-z.
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Abstract
BACKGROUND: Triggered monitoring in clinical trials is a risk-based monitoring approach where triggers (centrally monitored, predefined key risk and performance indicators) drive the extent, timing, and frequency of monitoring visits. The TEMPER study used a prospective, matched-pair design to evaluate the use of a triggered monitoring strategy, comparing findings from triggered monitoring visits with those from matched control sites. To facilitate this study, we developed a bespoke risk-based monitoring system: the TEMPER Management System. // METHODS: The TEMPER Management System comprises a web application (the front end), an SQL server database (the back end) to store the data generated for TEMPER, and a reporting function to aid users in study processes such as the selection of triggered sites. Triggers based on current practice were specified for three clinical trials and were implemented in the system. Trigger data were generated in the system using data extracted from the trial databases to inform the selection of triggered sites to visit. Matching of the chosen triggered sites with untriggered control sites was also performed in the system, while data entry screens facilitated the collection and management of the data from findings gathered at monitoring visits. // RESULTS: There were 38 triggers specified for the participating trials. Using these, 42 triggered sites were chosen and matched with control sites. Monitoring visits were carried out to all sites, and visit findings were entered into the TEMPER Management System. Finally, data extracted from the system were used for analysis. // CONCLUSIONS: The TEMPER Management System made possible the completion of the TEMPER study. It implemented an approach of standardising the automation of current-practice triggers, and the generation of trigger data to inform the selection of triggered sites to visit. It also implemented a matching algorithm informing the selection of matched control sites. We hope that by publishing this paper it encourages other trialists to share their approaches to, and experiences of, triggered monitoring and other risk-based monitoring systems.
| Type: | Article |
|---|---|
| Title: | Implementing monitoring triggers and matching of triggered and control sites in the TEMPER study: A description and evaluation of a triggered monitoring management system |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s13063-019-3301-z |
| Publisher version: | https://doi.org/10.1186/s13063-019-3301-z |
| Language: | English |
| Additional information: | This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| Keywords: | Triggered monitoring, Risk-based monitoring, Data management system |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10069837 |
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